Methods and Kits for Detecting Subjects at Risk of Having Cancer

ABSTRACT

The present invention relates to agents and methods for screening, diagnosis and surveillance of cancer, in particular pancreatic cancer.

CROSS REFERENCE TO RELATED APPLICATION

This application is a Divisional of U.S. application Ser. No.14/364,472, filed Jun. 11, 2014, which is the U.S. National Phase ofInternational Application No. PCT/US2012/68148, filed Dec. 6, 2012,which claims priority of U.S. Provisional Application No. 61/577,441,filed on Dec. 19, 2011, the contents of which are incorporated herein byreference in its entirety.

FIELD OF THE INVENTION

This invention relates to methods and agents for high risk screening,early diagnosis and surveillance of cancer, in particular pancreaticcancer.

BACKGROUND OF THE INVENTION

Cancer, also known as a malignant neoplasm, refers to disordersinvolving unregulated cell growth. In cancer, cells divide and growuncontrollably, forming malignant tumors, and invade nearby parts of thebody. The cancer may spread to distant parts of the body through thelymphatic system or bloodstream. Despite significant advances intherapeutics and diagnostics, cancer remains a major cause of morbidityand mortality in the U.S. For some cancers, despite these advances, theincidence is on the rise.

For example, pancreatic cancer represents an aggressive tumor with lessthan a 5% survival rate (Jemal et al., Cancer statistics CA Cancer JClin. 2009;59:225-249). Recent findings from Japan indicate that, withsmall tumors and no local infiltration, the survival rate can improve toover 20% (Tanaka et al. Pancreas 2004;28(3):268-72). Survival is betterupon early diagnosis. Unfortunately, the majority of pancreatic cancerpatients (85%) are diagnosed at late stage as diagnosis of pancreaticcancer at an early stage has met with several challenges including lackof biomarkers suitable for early detection and associated non-cancerouspancreatic diseases, which complicate early detection. Many moleculesfrom different classes have been interrogated as potential earlydetection markers, but yield no success.

Thus, there remains a need for agents and methods for high riskscreening, early diagnosis and surveillance of cancer, in particularpancreatic cancer.

SUMMARY OF INVENTION

This invention relates to agents and methods for high risk screening,early diagnosis and surveillance of cancer, in particular pancreaticcancer.

Accordingly, one aspect of the invention features a method fordetermining whether a subject has, or is at risk of having, a cellularproliferative disorder or a method for acquiring data or informationfrom such a subject. The method includes obtaining from the subject asample; and determining in vitro in the sample the expression level of amicroRNA, the microRNA being selected from (i) a first panel ofup-regulated microRNAs or (ii) a second panel of down-regulatedmicroRNAs. The subject or sample is classified or identified as to have,or to be at risk of having, the disorder such as pancreatic cancer if:(a) the expression level of the microRNA selected from the first panelis above a first predetermined reference value, or (b) the expressionlevel of the microRNA selected from the second panel is below a secondpredetermined reference value. Examples of microRNAs of the first andsecond panels include those listed in Table 2. Additional examples ofthe first panel include miR-18a, miR-22, miR-486, miR-642b, miR-7, andmiR-885-5p.

In one preferred embodiment, the method includes steps of obtaining fromthe subject a sample; and determining in the sample the expression levelof a first microRNA. The first microRNA is selected from a panel ofup-regulated microRNAs consisting of miR-18a, miR-22, miR-486, miR-642b,miR-7, and miR-885-5p. The subject or sample is classified or identifiedas to have, or to be at risk of having, the cellular proliferativedisorder if the expression level of the first microRNA in the sample isabove a predetermined reference value.

A cellular proliferative disorder refers to a disorder characterized byuncontrolled, autonomous cell growth, including non-malignant andmalignant growth disorder, such as cancer or neoplastic diseases.Examples of the cellular proliferative disorder include pancreaticcancer, colon cancer, breast cancer, prostate cancer, hepatocellularcarcinoma, melanoma, lung cancer, glioblastoma, brain tumor,hematopoietic malignancies, retinoblastoma, renal cell carcinoma, headand neck cancer, cervical cancer, esophageal cancer, and squamous cellcarcinoma. In one embodiment, the disorder is a pancreatic cancer. Inthe method, the predetermined reference value can be obtained from acontrol subject that does not have the disorder; the subject can be onewith a high risk of having the disorder. The sample can be any suitablesample, such as a body fluid sample. Examples of the body fluid includeblood, serum, and plasma. In one example, the sample contains pancreatictissue, pancreatic tumor, pancreatic cells, or pancreatic juice. Themethod can further include determining in the sample the expressionlevel of a second microRNA.

In a second aspect, the invention features an array. The array includes,among others, a support having a plurality of unique locations, and anycombination of (i) at least one nucleic acid having a sequence that iscomplementary to a microRNA selected from the above-mentioned firstpanel of up-regulated microRNAs or (ii) at least one nucleic acid havinga sequence that is complementary to a microRNA selected from theabove-mentioned second panel of down-regulated microRNAs, wherein eachnucleic acid is immobilized to a unique location of the support. In apreferred embodiment, the array includes a support having a plurality ofunique locations, and any combination of at least one nucleic acidhaving a sequence that is complementary to a microRNA selected from apanel of up-regulated microRNAs, where each nucleic acid is immobilizedto a unique location of the support. The panel can include miR-18a,miR-22, miR-486, miR-642b, miR-7, and miR-885-5p. In one example, thenucleic acid is complementary to a sequence selected from the groupconsisting of SEQ ID NOs: 1-6. Other exemplary microRNAs include thoseshown in Table 2 below, where 116 miRNAs are ranked based on thesignificance in fold change between Pancreatic Cancer and HealthyControl or between High Risk Group and Healthy Control. Of these 116significant mi-RNAs, at least the top 30 miRNAs showed about 2 folds ormore changes (up or down) and are preferred. As shown in Table 2, themicroRNAs can be grouped into two panels based on their values for “FoldChange between Pancreatic Cancer and Healthy Control.” Specifically, themicroRNAs in the first panel were unregulated in the pancreatic cancerpatients and their “Fold Change vs Pancreatic Cancer and HealthyControl” values are greater than 1.0; the microRNAs in the second panelwere down-regulated in the pancreatic cancer patients and their “FoldChange vs Pancreatic Cancer and Healthy Control” values are less than1.0.

In a third aspect, the invention provides a kit that contains a probehaving a nucleic acid sequence that is complementary to the sequence ofa microRNA selected from (i) the first panel of up-regulated microRNAsor (ii) the second panel of down-regulated microRNAs or a pair of PCRprimers for amplifying said microRNA. In a preferred embodiment, thenucleic acid sequence that is complementary to the sequence of microRNAselected from panel of up-regulated microRNAs or a pair of PCR primersfor amplifying said microRNA. The panel can include miR-18a, miR-22,miR-486, miR-642b, miR-7, and miR-885-5p. In one example, the probe iscomplementary to a sequence selected from the group consisting of SEQ IDNOs: 1-6. The kit can further contain reagents for performinghybridization, reagents for performing PCR, or the above-disclosedarray.

The invention also features (i) a method for determining whether asubject has, or is at risk of having, a cellular proliferative disorder,substantially as shown and described herein and (ii) an array or kitsubstantially as shown and described herein.

In the above methods, the identifying or classifying step can furtherinclude generating, or otherwise communicating to a third person, areport specifying that the sample or the subject has, or is at risk ofhaving, the disorder or, for the prognosis method, that the subjectunder a treatment has a good or poor prognosis. In the methods mentionedabove, the sample can also be a surgically or endoscopically resectedpancreatic tissue sample. Examples of the sample include pancreatictissue, pancreatic tumor, pancreatic cells, pancreatic cyst fluid, orpancreatic juice. The sample can be a body fluid sample (e.g., blood,serum, and plasma from the pancreas). In a preferred embodiment, thesample is selected from the group consisting of blood, serum, plasma,pancreatic cyst fluid, and pancreatic juice.

The details of one or more embodiments of the invention are set forth inthe description below. Other features, objects, and advantages of theinvention will be apparent from the description and from the claims.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a diagram showing results of unsupervised cluster analysisrevealed a significant (FDR<10%) and differentially regulated (>2-fold)miRNA signature comprising of 14 members that segregated pancreaticcancer patients away from not only healthy individuals but alsohigh-risk subjects. These 14 significant microRNAs were identified frommicroarray experiments that probed the entire Sanger miRBASE version 16.MicroRNA probe expression values (Log2 transformed & normalizedmicroarray probe intensities) of selected microRNA in Cancer, High Riskand Control samples were median centered. Each column represents asingle sample, and each row represents a single microRNA probe. Greensquares represent lower than median levels of microRNA expression; blacksquares represent median levels of microRNA expression; red squaresrepresent higher than median levels of microRNA expression. Legendunits: 1.0=differs from median probe intensity by one log 2 unit(2-fold)

DETAILED DESCRIPTION OF THE INVENTION

This invention is based, at least in part, on an unexpected discovery ofa number of microRNA gene products whose expression levels are alteredin biological samples obtained from subjects with cancer, such aspancreatic cancer, relative to control samples. These genes can be usedas biomarkers for determining whether a subject has, or is at risk ofhaving, a cellular proliferative disorder or for determining a prognosisor surveillance of patient having such a disorder.

Accordingly, the present invention encompasses methods of diagnosingwhether a subject has, or is at risk for, a cellular proliferativedisorder, such as cancer or neoplastic diseases. The term “neoplasticdiseases” refers to cancers of any kind and origin and precursor stagesthereof. The term “neoplastic disease” includes the subject matteridentified by the terms “neoplasia,” “neoplasm,” “cancer,” “pre-cancer,”or “tumor.” A neoplastic disease is generally manifest by abnormal celldivision resulting in an abnormal level of a particular cell population.The abnormal cell division underlying a neoplastic disease is typicallyinherent in the cells and not a normal physiological response toinfection or inflammation. In some embodiments, neoplastic diseases fordiagnosis using methods provided herein include carcinoma. By“carcinoma,” it is meant a benign or malignant epithelial tumor andincludes, but is not limited to, hepatocellular carcinoma, breastcarcinoma, prostate carcinoma, non-small cell lung carcinoma, coloncarcinoma, CNS carcinoma, melanoma, ovarian carcinoma, or renalcarcinoma. An exemplary neoplastic disease is pancreatic cancer,including adenocarcinoma and neuroendocrine tumor.

The invention also provides for methods of screening subjects who arethought to be at risk for developing the above-mentioned cancer, e.g.,pancreatic cancer. Also provided are methods of determining the efficacyof therapeutic regimens for inhibiting the cancer, and methods ofidentifying an anti-cancer agent. The invention also encompasses variouskits suitable for carrying out the above mentioned methods.

MicroRNA Genes

As disclosed herein, a number of microRNA genes were identified based ontheir altered expression patterns in cancer patients and healthysubject. As used herein interchangeably, “microRNA,” “miR,” or “miRNA”refers to the unprocessed or processed RNA transcript from a miRNA gene.The unprocessed miRNA gene transcript is also called a “miRNAprecursor,” and typically comprises an RNA transcript of about 70-100nucleotides in length. The miRNA precursor can be processed by digestionwith an RNAse (for example, Dicer, Argonaut, or RNAse III) into anactive 18-25 nucleotide RNA molecule. This active 18-25 nucleotide RNAmolecule is also called the “processed” miRNA gene transcript or“mature” miRNA.

The microRNA genes of this invention can be divided into two groups. Inone embodiment, the level of a miR gene product in a test sample from apatient is greater than the level of the corresponding miR gene productin a control sample (i.e., expression of the miR gene product is“up-regulated” or “over-expressed”). As used herein, expression of anmiR gene product is “up-regulated” when the amount of miR gene productin a test sample from a subject is greater than the amount of the samegene product in a control sample. Examples of these up-regulatedmicroRNAs include SEQ ID NOs:1-6 listed in Table 1 below.

TABLE 1 SEQ S16_hsa_miRNA_name S16_hsa_MIMAT_ID S16_hsa_miRNA_sequenceID NO: hsa-miR-18a MIMAT0000072 UAAGGUGCAUCUAGUGCAGAUAG 1 hsa-miR-22MIMAT0000077 AAGCUGCCAGUUGAAGAACUGU 2 hsa-miR-486-5p MIMAT0002177UCCUGUACUGAGCUGCCCCGAG 3 hsa-miR-642b MIMAT0018444AGACACAUUUGGAGAGGGACCC 4 hsa-miR-7 MIMAT0000252 UGGAAGACUAGUGAUUUUGUUGU5 hsa-miR-885-5p MIMAT0004947 UCCAUUACACUACCCUGCCUCU 6 hsa-miR-3196MIMAT0015080 CGGGGCGGCAGGGGCCUC 7

These genes can be used in diagnosing cancer based on increases in theirexpression levels. Other up-regulated microRNAs that can be used includethose described in Ho et al., Transl Oncol. 2010;3:109-113; Wang et al.Cancer Prey Res (Phila). 2009 Sep;2(9):807-13; Lee et al. Int. J.Cancer. 2007, 120(5):1046-1054; and US Application 20110171646. All ofthese references cited herein are incorporated herein in theirentireties. The relative miR gene expression in the control samples canbe determined with respect to one or more RNA expression standards. Thestandards can comprise, for example, the average level of miR geneexpression previously obtained for a population of normal controls.

In other embodiments, the level of a target miR gene product in the testsample is less than the level of the corresponding miR gene product inthe control sample (i.e., expression of the miR gene product is“down-regulated” or “under-expressed”). As used herein, expression of amiR gene is “down-regulated” when the amount of miR gene product in atest sample from a subject is less than the amount of the same geneproduct in a control sample.

Diagnosis and Prognosis Methods

The above-describe genes, related kits or arrays, can be used indetermining whether a subject has, or is at risk of having, a cellularproliferative disorder. Alternatively, they can be used for determininga prognosis of such a disorder in a subject.

Diagnosis Methods

In one aspect, the invention provides qualitative and quantitativeinformation to determine whether a subject has or is predisposed to adisease characterized by uncontrolled, autonomous cell growth, e.g.,cancer. A subject having a cellular proliferative disorder or prone toit can be determined based on the expression levels, patterns, orprofiles of the above-described genes or their products (microRNA) in atest sample from the subject. In other words, the products can be usedas markers to indicate the presence or absence of the disorder.Diagnostic and prognostic assays of the invention include methods forassessing the expression level of the products. The methods and kitsallow one to detect cellular proliferative disorders, such as cancer.For example, a relative increase in the expression level of one or moreup-regulated genes is indicative of presence the disorder. Conversely, alower expression level or a lack of the expression is indicative lack ofthe disorder.

The presence, level, or absence of the microRNA products in a testsample can be evaluated by obtaining a test sample from a test subjectand contacting the test sample with a compound or an agent capable ofdetecting the nucleic acid (e.g., RNA or DNA probe). The “test sample”includes tissues, cells and biological fluids isolated from a subject,as well as tissues, cells and fluids present within a subject. The levelof expression of a gene(s) of interest can be measured in a number ofways, including measuring the RNA encoded by the gene.

Expressed RNA samples can be isolated from biological samples using anyof a number of well-known procedures. For example, biological samplescan be lysed in a guanidinium-based lysis buffer, optionally containingadditional components to stabilize the RNA. In some embodiments, thelysis buffer can contain purified RNAs as controls to monitor recoveryand stability of RNA from cell cultures. Examples of such purified RNAtemplates include the Kanamycin Positive Control RNA from PROMEGA(Madison, Wis.), and 7.5 kb Poly(A)-Tailed RNA from LIFE TECHNOLOGIES(Rockville, Md.). Lysates may be used immediately or stored frozen at,e.g., -80° C.

Optionally, total RNA can be purified from cell lysates (or other typesof samples) using silica-based isolation in an automation-compatible,96-well format, such as the RNEASY purification platform (QIAGEN, Inc.,Valencia, Calif.). Other RNA isolation methods are contemplated, such asextraction with silica-coated beads or guanidinium. Further methods forRNA isolation and preparation can be devised by one skilled in the art.

The methods of the present invention can be performed using crudesamples (e.g., blood, serum, plasma, or cell lysates), eliminating theneed to isolate RNA. RNAse inhibitors are optionally added to the crudesamples. When using crude cellular lysates, it should be noted thatgenomic DNA can contribute one or more copies of a target sequence,e.g., a gene, depending on the sample. In situations in which the targetsequence is derived from one or more highly expressed genes, the signalarising from genomic DNA may not be significant. But for genes expressedat low levels, the background can be eliminated by treating the sampleswith DNAse, or by using primers that target splice junctions forsubsequent priming of cDNA or amplification products.

The level of RNA corresponding to a gene in a cell can be determinedboth in situ and in vitro. RNA isolated from a test sample can be usedin hybridization or amplification assays that include, Southern orNorthern analyses, PCR analyses, and probe arrays. A preferreddiagnostic method for the detection of RNA levels involves contactingthe isolated RNA with a nucleic acid probe that can hybridize to the RNAencoded by the gene. The probe can be a full-length nucleic acid or aportion thereof, such as an oligonucleotide of at least 10 nucleotidesin length and sufficient to specifically hybridize under stringentconditions to the RNA.

In one format, RNA (or cDNA prepared from it) is immobilized on asurface and contacted with the probes, for example, by running theisolated RNA on an agarose gel and transferring the RNA from the gel toa membrane, such as nitrocellulose. In another format, the probes areimmobilized on a surface and the RNA (or cDNA) is contacted with theprobes, for example, in a gene chip array. A skilled artisan can adaptknown RNA detection methods for detecting the level of RNA.

The level of RNA (or cDNA prepared from it) in a sample encoded by agene to be examined can be evaluated with nucleic acid amplification,e.g., by standard PCR (U.S. Pat. No. 4,683,202), RT-PCR (Bustin S. J MolEndocrinol. 25:169-93, 2000), quantitative PCR (Ong Y. et al.,Hematology. 7:59-67, 2002), real time PCR (Ginzinger D. Exp Hematol.30:503-12, 2002), and in situ PCR (Thaker V. Methods Mol Biol.115:379-402, 1999), or any other nucleic acid amplification method,followed by the detection of the amplified molecules using techniquesknown in the art.

In another embodiment, the methods of the invention further includecontacting a control sample with a compound or agent capable ofdetecting the RNA of a gene and comparing the presence of the RNA in thecontrol sample with the presence of the RNA in the test sample.

The above-described methods and markers can be used to assess the riskof a subject for developing a cellular proliferative disorder, includingcancer such as pancreatic cancer. In particular, the invention can beapplied to those in high risk cohort who already have certain risks soas to gain critical insight into early detection. For example,approximately 10% of pancreatic cancers are hereditary in origin (Kleinet al. Cancer J 2001;7:266-73; Bartsch et al. Int J Cancer2004;110:902-6; and Hemminki et al. Int J Cancer 2003;103:525-30) and insome individuals the lifetime risk of pancreatic cancer approaches 50%(Rulyak et al. Pancreatology 2001;1(5):477-85), a microRNA signature forscreening and surveillance would be significant.

As used herein “one with a high risk of having pancreatic cancer” toinclude individuals who meet one or more of the following criteria.

1. Individuals with two or more first degree relatives with pancreaticcancer;

2. Individuals with one first degree relative diagnosed with pancreaticcancer at an early age (under the age of 50);

3. Individuals with two or more second degree relatives with pancreaticcancer, one of whom developed it at an early age (under the age of 60);

4. Members of families affected by BRCA I and BRCA II mutations;

5. Members of families with familial atypical multiple-mole melanoma(FAMM) syndromes;

6. Having heredity pancreatitis;

7. Having HNPCC Syndrome;

8. Having Familial Adenomatous Polyposis (FAP) Syndrome;

9. Having Peutz-Jeghers Syndrome; and

10. Patients who have been found with abnormal ultrasonography or CTimaging of the pancreas through routine examinations with conventionalmethod.

A change in levels of miR gene products associated with pancreaticcancer can be detected prior to, or in the early stages of, thedevelopment of transformed or neoplastic phenotypes in cells of asubject. The invention therefore also provides a method for screening asubject who is at risk of developing pancreatic cancer, comprisingevaluating the level of at least one miR gene product, or a combinationof miR gene products, associated with pancreatic cancer in a biologicalsample obtained form the subject's pancreas. Accordingly, an alterationin the level of the miR gene product, or combination of miR geneproducts, in the biological sample as compared to the level of acorresponding miR gene product in a control sample, is indicative of thesubject being at risk for developing pancreatic cancer. The biologicalsample used for such screening can include pancreatic tissue that iseither normal or suspected to be precancerous. Subjects with a change inthe level of one or more miR gene products associated with pancreaticcancer are candidates for further monitoring and testing. Such furthertesting can comprise histological examination of tissue samples, orother techniques within the skill in the art.

As used herein, the term “diagnosis” means detecting a disease ordisorder or determining the stage or degree of a disease or disorder.Usually, a diagnosis of a disease or disorder is based on the evaluationof one or more factors and/or symptoms that are indicative of thedisease. That is, a diagnosis can be made based on the presence, absenceor amount of a factor which is indicative of presence or absence of thedisease or condition. Each factor or symptom that is considered to beindicative for the diagnosis of a particular disease does not need beexclusively related to the particular disease; i.e. there may bedifferential diagnoses that can be inferred from a diagnostic factor orsymptom. Likewise, there may be instances where a factor or symptom thatis indicative of a particular disease is present in an individual thatdoes not have the particular disease. The diagnostic methods may be usedindependently, or in combination with other diagnosing and/or stagingmethods known in the medical art for a particular disease or disorder,e.g., pancreatic cancer.

Prognosis Methods

The diagnostic methods described above can identify subjects having, orat risk of developing, a disease or disorder associated with cellularproliferative disorder. In addition, changes in expression levels and/ortrends of the above-mentioned genes (or a subset of it) in a biologicalsample, e.g., peripheral blood samples, can provide an early indicationof recovery or lack thereof. For example, a further increase (ordecline) or persistently-altered gene expression levels of theunregulated genes (or down-regulated genes) indicate a poor prognosis,i.e., lack of improvement or health decline. Accordingly, these genesallow one to assess post-treatment recovery of cancer. The analysis ofthis select group of genes or a subset thereof indicates outcomes of theconditions.

The prognostic assays described herein can be used to determine whethera subject is suitable to be administered with an agent (e.g., anagonist, antagonist, peptidomimetic, protein, peptide, nucleic acid,small molecule, or other drug candidate) to treat a disorder associatedwith uncontrolled, autonomous cell growth. For example, such assays canbe used to determine whether a subject can be administered with achemotherapeutic agent

Thus, also provided by this invention is a method of monitoring atreatment for a cellular proliferative disorder in a subject. For thispurpose, gene expression levels of the genes disclosed herein can bedetermined for test samples from a subject before, during, or afterundergoing a treatment. The magnitudes of the changes in the levels ascompared to a baseline level are then assessed. A decrease of themagnitudes of the changes after the treatment indicates that the subjectcan be further treated by the same treatment. For example, a relativedecrease in the expression level of one or more up-regulated genes isindicative of recovery from the disorder. Conversely, further increaseor persistent high expression levels of one or more of the up-regulatedgenes is indicate lack of improvement or health decline.

Information obtained from practice of the above assays is useful inprognostication, identifying progression of, and clinical management ofdiseases and other deleterious conditions affecting an individualsubject's health status. In preferred embodiments, the foregoingdiagnostic assays provide information useful in prognostication,identifying progression of and management of conditions that arecharacterized by uncontrolled, autonomous cell growth. The informationmore specifically assists the clinician in designing chemotherapeutic orother treatment regimes to eradicate such conditions from the body of anafflicted subject, a human.

The term “prognosis” as used herein refers to a prediction of theprobable course and outcome of a clinical condition or disease. Aprognosis is usually made by evaluating factors or symptoms of a diseasethat are indicative of a favorable or unfavorable course or outcome ofthe disease. The phrase “determining the prognosis” as used hereinrefers to the process by which the skilled artisan can predict thecourse or outcome of a condition in a patient. The term “prognosis” doesnot refer to the ability to predict the course or outcome of a conditionwith 100% accuracy instead, the skilled artisan will understand that theterm “prognosis” refers to an increased probability that a certaincourse or outcome will occur; that is, that a course or outcome is morelikely to occur in a patient exhibiting a given condition, when comparedto those individuals not exhibiting the condition.

The terms “favorable prognosis” and “positive prognosis,” or“unfavorable prognosis” and “negative prognosis” as used herein arerelative terms for the prediction of the probable course and/or likelyoutcome of a condition or a disease. A favorable or positive prognosispredicts a better outcome for a condition than an unfavorable ornegative prognosis. In a general sense, a “favorable prognosis” is anoutcome that is relatively better than many other possible prognosesthat could be associated with a particular condition, whereas anunfavorable prognosis predicts an outcome that is relatively worse thanmany other possible prognoses that could be associated with a particularcondition. Typical examples of a favorable or positive prognosis includea better than average cure rate, a lower propensity for metastasis, alonger than expected life expectancy, differentiation of a benignprocess from a cancerous process, and the like. For example, a positiveprognosis is one where a patient has a 50% probability of being cured ofa particular cancer after treatment, while the average patient with thesame cancer has only a 25% probability of being cured.

The terms “determining,” “measuring,” “assessing,” and “assaying” areused interchangeably and include both quantitative and qualitativemeasurement, and include determining if a characteristic, trait, orfeature is present or not. Assessing may be relative or absolute.“Assessing the presence of” a target includes determining the amount ofthe target present, as well as determining whether it is present orabsent.

Arrays

Also provided in the invention is a biochip or array. The biochip/arraymay contain a solid or semi-solid substrate having an attached probe orplurality of probes described herein. The probes may be capable ofhybridizing to a target sequence under stringent hybridizationconditions. The probes may be attached at spatially defined address onthe substrate. More than one probe per target sequence may be used, witheither overlapping probes or probes to different sections of aparticular target sequence. The probes may be capable of hybridizing totarget sequences associated with a single disorder appreciated by thosein the art. The probes may either be synthesized first, with subsequentattachment to the biochip, or may be directly synthesized on thebiochip.

“Attached” or “immobilized” as used herein to refer to a nucleic acid(e.g., a probe) and a solid support may mean that the binding betweenthe probe and the solid support is sufficient to be stable underconditions of binding, washing, analysis, and removal. The binding maybe covalent or non-covalent. Covalent bonds may be formed directlybetween the probe and the solid support or may be formed by a crosslinker or by inclusion of a specific reactive group on either the solidsupport or the probe or both molecules. Non-covalent binding may be oneor more of electrostatic, hydrophilic, and hydrophobic interactions.Included in non-covalent binding is the covalent attachment of amolecule, such as streptavidin, to the support and the non-covalentbinding of a biotinylated probe to the streptavidin. Immobilization mayalso involve a combination of covalent and non-covalent interactions.

The solid substrate can be a material that may be modified to containdiscrete individual sites appropriate for the attachment or associationof the probes and is amenable to at least one detection method. Examplesof such substrates include glass and modified or functionalized glass,plastics (including acrylics, polystyrene and copolymers of styrene andother materials, polypropylene, polyethylene, polybutylene,polyurethanes, TeflonJ, etc.), polysaccharides, nylon or nitrocellulose,resins, silica or silica-based materials including silicon and modifiedsilicon, carbon, metals, inorganic glasses and plastics. The substratesmay allow optical detection without appreciably fluorescing.

The substrate can be planar, although other configurations of substratesmay be used as well. For example, probes may be placed on the insidesurface of a tube, for flow-through sample analysis to minimize samplevolume. Similarly, the substrate may be flexible, such as flexible foam,including closed cell foams made of particular plastics.

The array/biochip and the probe may be derivatized with chemicalfunctional groups for subsequent attachment of the two. For example, thebiochip may be derivatized with a chemical functional group including,but not limited to, amino groups, carboxyl groups, oxo groups or thiolgroups. Using these functional groups, the probes may be attached usingfunctional groups on the probes either directly or indirectly using alinker. The probes may be attached to the solid support by either the 5′terminus, 3′ terminus, or via an internal nucleotide. The probe may alsobe attached to the solid support non-covalently. For example,biotinylated oligonucleotides can be made, which may bind to surfacescovalently coated with streptavidin, resulting in attachment.Alternatively, probes may be synthesized on the surface using techniquessuch as photopolymerization and photolithography. Detailed discussion ofmethods for linking nucleic acids to a support substrate can be foundin, e.g., U.S. Pat. Nos. 5,837,832, 6,087,112, 5,215,882, 5,707,807,5,807,522, 5,958,342, 5,994,076, 6,004,755, 6,048,695, 6,060,240,6,090,556, and 6,040,138.

In some embodiments, an expressed transcript (e.g., a transcript of amicroRNA gene described herein) is represented in the nucleic acidarrays. In such embodiments, a set of binding sites can include probeswith different nucleic acids that are complementary to differentsequence segments of the expressed transcript. Examples of such nucleicacids can be of length of 15 to 200 bases, 20 to 100 bases, 25 to 50bases, 40 to 60 bases. Each probe sequence can also include one or morelinker sequences in addition to the sequence that is complementary toits target sequence. A linker sequence is a sequence between thesequence that is complementary to its target sequence and the surface ofsupport. For example, the nucleic acid arrays of the invention can haveone probe specific to each target microRNA gene. However, if desired,the nucleic acid arrays can contain at least 2, 5, 10, 100, 200, 300,400, 500 or more probes specific to some expressed transcript (e.g., atranscript of a microRNA gene described herein, e.g., SEQ ID NOs: 1-6).

Kits

In another aspect, the present invention provides kits embodying themethods, compositions, and systems for analysis of microRNA geneexpression as described herein.

Such a kit may contain a nucleic acid described herein together with anyor all of the following: assay reagents, buffers, probes and/or primers,and sterile saline or another pharmaceutically acceptable emulsion andsuspension base. In addition, the kit may include instructionalmaterials containing directions (e.g., protocols) for the practice ofthe methods described herein. For example, the kit may be a kit for theamplification, detection, identification or quantification of a targetmicroRNA sequence. To that end, the kit may contain a suitable primer(e.g., hairpin primers), a forward primer, a reverse primer, and aprobe.

In one example, a kit of the invention includes one or more microarrayslides (or alternative microarray format) onto which a plurality ofdifferent nucleic acids (each corresponding to one of theabove-mentioned genes) have been deposited. The kit can also include aplurality of labeled probes. Alternatively, the kit can include aplurality of polynucleotide sequences suitable as probes and a selectionof labels suitable for customizing the included polynucleotidesequences, or other polynucleotide sequences at the discretion of thepractitioner. Commonly, at least one included polynucleotide sequencecorresponds to a control sequence, e.g., a normalization gene or thelike. Exemplary labels include, but are not limited to, a fluorophore, adye, a radiolabel, an enzyme tag, that is linked to a nucleic acidprimer.

In one embodiment, kits that are suitable for amplifying nucleic acidcorresponding to the expressed RNA samples are provided. Such a kitincludes reagents and primers suitable for use in any of theamplification methods described above. Alternatively, or additionally,the kits are suitable for amplifying a signal corresponding tohybridization between a probe and a target nucleic acid sample (e.g.,deposited on a microarray).

In addition, one or more materials and/or reagents required forpreparing a biological sample for gene expression analysis areoptionally included in the kit. Furthermore, optionally included in thekits are one or more enzymes suitable for amplifying nucleic acids,including various polymerases (RT, Taq, etc.), one or moredeoxynucleotides, and buffers to provide the necessary reaction mixturefor amplification.

Typically, the kits are employed for analyzing gene expression patternsusing microRNA as the starting template. The mRNA template may bepresented as either total cellular RNA or isolated microRNA; both typesof sample yield comparable results. In other embodiments, the methodsand kits described in the present invention allow quantitation of otherproducts of gene expression, including tRNA, rRNA, or othertranscription products.

Optionally, the kits of the invention further include software toexpedite the generation, analysis and/or storage of data, and tofacilitate access to databases. The software includes logicalinstructions, instructions sets, or suitable computer programs that canbe used in the collection, storage and/or analysis of the data.Comparative and relational analysis of the data is possible using thesoftware provided.

The kits optionally contain distinct containers for each individualreagent and/or enzyme component. Each component will generally besuitable as aliquoted in its respective container. The container of thekits optionally includes at least one vial, ampule, or test tube.Flasks, bottles and other container mechanisms into which the reagentscan be placed and/or aliquoted are also possible. The individualcontainers of the kit are preferably maintained in close confinement forcommercial sale. Suitable larger containers may include injection orblow-molded plastic containers into which the desired vials areretained. Instructions, such as written directions or videotapeddemonstrations detailing the use of the kits of the present invention,are optionally provided with the kit.

In a further aspect, the present invention provides for the use of anycomposition or kit herein, for the practice of any method or assayherein, and/or for the use of any apparatus or kit to practice any assayor method herein.

A “subject” refers to a human and a non-human animal. Examples of anon-human animal include all vertebrates, e.g., mammals, such asnon-human mammals, non-human primates (particularly higher primates),dog, rodent (e.g., mouse or rat), guinea pig, cat, and rabbit, andnon-mammals, such as birds, amphibians, reptiles, etc. In oneembodiment, the subject is a human. In another embodiment, the subjectis an experimental, non-human animal or animal suitable as a diseasemodel.

A “test sample” or a “biological sample” as used herein may mean asample of biological tissue or fluid that comprises nucleic acids. Suchsamples include, but are not limited to, tissue or body fluid isolatedfrom animals. Biological samples may also include sections of tissuessuch as biopsy and autopsy samples, frozen sections taken forhistological purposes, blood, plasma, serum, sputum, stool, tears,mucus, urine, effusions, amniotic fluid, ascitic fluid, hair, and skin.Biological samples also include explants and primary and/or transformedcell cultures derived from patient tissues. A biological sample may beprovided by removing a sample of cells from an animal, but can also beaccomplished by using previously isolated cells (e.g., isolated byanother person, at another time, and/or for another purpose), or byperforming the methods described herein in vivo. Archival tissues, suchas those having treatment or outcome history, may also be used.

The term “body fluid” or “bodily fluid” refers to any fluid from thebody of an animal. Examples of body fluids include, but are not limitedto, plasma, serum, blood, lymphatic fluid, cerebrospinal fluid, synovialfluid, urine, saliva, mucous, phlegm and sputum. A body fluid sample maybe collected by any suitable method. The body fluid sample may be usedimmediately or may be stored for later use. Any suitable storage methodknown in the art may be used to store the body fluid sample: forexample, the sample may be frozen at about −20° C. to about −70° C.Suitable body fluids are acellular fluids. “Acellular” fluids includebody fluid samples in which cells are absent or are present in such lowamounts that the miRNA level determined reflects its level in the liquidportion of the sample, rather than in the cellular portion. Suchacellular body fluids are generally produced by processing acell-containing body fluid by, for example, centrifugation orfiltration, to remove the cells. Typically, an acellular body fluidcontains no intact cells however, some may contain cell fragments orcellular debris. Examples of acellular fluids include plasma or serum,or body fluids from which cells have been removed.

The term “gene” used herein refers to a natural (e.g., genomic) orsynthetic gene comprising transcriptional and/or translationalregulatory sequences and/or a coding region and/or non-translatedsequences (e.g., introns, 5′- and 3′-untranslated sequences). The codingregion of a gene may be a nucleotide sequence coding for an amino acidsequence or a functional RNA, such as tRNA, rRNA, catalytic RNA, siRNA,miRNA or antisense RNA. A gene may also be an mRNA or cDNA correspondingto the coding regions (e.g., exons and miRNA) optionally comprising 5′-or 3′-untranslated sequences linked thereto. A gene may also be anamplified nucleic acid molecule produced in vitro comprising all or apart of the coding region and/or 5′- or 3′-untranslated sequences linkedthereto. The term also includes pseudogenes, which are dysfunctionalrelatives of known genes that have lost their protein-coding ability orare otherwise no longer expressed in a cell.

“Expression profile” refers to a genomic expression profile, e.g., anexpression profile of microRNAs. Profiles may be generated by anyconvenient means for determining a level of a nucleic acid sequencee.g., quantitative hybridization of microRNA, cRNA, etc., quantitativePCR, ELISA for quantification, and the like, and allow the analysis ofdifferential gene expression between two samples. A subject or patientsample, e.g., cells or a collection thereof, e.g., tissues, is assayed.Samples are collected by any convenient method known in the art. Nucleicacid sequences of interest are nucleic acid sequences that are found tobe predictive, including the nucleic acid sequences of those describedherein, where the expression profile may include expression data for 5,10, 20, 25, 50, 100 or more of, including all of the listed nucleic acidsequences. The term “expression profile” may also mean measuring theabundance of the nucleic acid sequences in the measured samples.

“Differential expression” refers to qualitative or quantitativedifferences in the temporal and/or cellular gene expression patternswithin and among cells and tissue. Thus, a differentially expressed genecan qualitatively have its expression altered, including an activationor inactivation, in, e.g., normal versus disease tissue. Genes may beturned on or turned off in a particular state, relative to another statethus permitting comparison of two or more states. A qualitativelyregulated gene will exhibit an expression pattern within a state or celltype that may be detectable by standard techniques. Some genes will beexpressed in one state or cell type, but not in both. Alternatively, thedifference in expression may be quantitative, e.g., in that expressionis modulated, up-regulated, resulting in an increased amount oftranscript, or down-regulated, resulting in a decreased amount oftranscript. The degree to which expression differs need only be largeenough to quantify via standard characterization techniques such asexpression arrays, quantitative reverse transcriptase PCR, Northernanalysis, and RNase protection.

“Nucleic acid” or “oligonucleotide” or “polynucleotide” as used hereinrefers to at least two nucleotides covalently linked together. Thedepiction of a single strand also defines the sequence of thecomplementary strand. Thus, a nucleic acid also encompasses thecomplementary strand of a depicted single strand. Many variants of anucleic acid may be used for the same purpose as a given nucleic acid.Thus, a nucleic acid also encompasses substantially identical nucleicacids and complements thereof. A single strand provides a probe that mayhybridize to a target sequence under stringent hybridization conditions.Thus, a nucleic acid also encompasses a probe that hybridizes understringent hybridization conditions.

Nucleic acids may be single stranded or double stranded, or may containportions of both double stranded and single stranded sequence. Thenucleic acid may be DNA, both genomic and cDNA, RNA, or a hybrid, wherethe nucleic acid may contain combinations of deoxyribo- andribo-nucleotides, and combinations of bases including uracil, adenine,thymine, cytosine, guanine, inosine, xanthine hypoxanthine, isocytosineand isoguanine. Nucleic acids may be obtained by chemical synthesismethods or by recombinant methods.

The term “primer” refers to any nucleic acid that is capable ofhybridizing at its 3′ end to a complementary nucleic acid molecule, andthat provides a free 3′ hydroxyl terminus which can be extended by anucleic acid polymerase. As used herein, amplification primers are apair of nucleic acid molecules that can anneal to 5′ or 3′ regions of agene (plus and minus strands, respectively, or vice-versa) and contain ashort region in between. Under appropriate conditions and withappropriate reagents, such primers permit the amplification of a nucleicacid molecule having the nucleotide sequence flanked by the primers. Forin situ methods, a cell or tissue sample can be prepared and immobilizedon a support, such as a glass slide, and then contacted with a probethat can hybridize to RNA. Alternative methods for amplifying nucleicacids corresponding to expressed RNA samples include those described in,e.g., U.S. Pat. No. 7,897,750.

The term “probe” as used herein refers to an oligonucleotide capable ofbinding to a target nucleic acid of complementary sequence through oneor more types of chemical bonds, usually through complementary basepairing, usually through hydrogen bond formation. Probes may bind targetsequences lacking complete complementarity with the probe sequencedepending upon the stringency of the hybridization conditions. There maybe any number of base pair mismatches which will interfere withhybridization between the target sequence and the single strandednucleic acids described herein. However, if the number of mutations isso great that no hybridization can occur under even the least stringentof hybridization conditions, the sequence is not a complementary targetsequence. A probe may be single stranded or partially single andpartially double stranded. The strandedness of the probe is dictated bythe structure, composition, and properties of the target sequence.Probes may be directly labeled or indirectly labeled such as with biotinto which a streptavidin complex may later bind.

“Complement” or “complementary” as used herein to refer to a nucleicacid may mean Watson-Crick (e.g., A-T/U and C-G) or Hoogsteen basepairing between nucleotides or nucleotide analogs of nucleic acidmolecules. A full complement or fully complementary may mean 100%complementary base pairing between nucleotides or nucleotide analogs ofnucleic acid molecules.

“Stringent hybridization conditions” as used herein refers to conditionsunder which a first nucleic acid sequence (e.g., probe) hybridizes to asecond nucleic acid sequence (e.g., target), such as in a complexmixture of nucleic acids. Stringent conditions are sequence- dependentand be different in different circumstances, and can be suitablyselected by one skilled in the art. Stringent conditions may be selectedto be about 5-10° C. lower than the thermal melting point (Tm) for thespecific sequence at a defined ionic strength pH. The Tm may be thetemperature (under defined ionic strength, pH, and nucleicconcentration) at which 50% of the probes complementary to the targethybridize to the target sequence at equilibrium (as the target sequencesare present in excess, at Tm, 50% of the probes are occupied atequilibrium). Stringent conditions may be those in which the saltconcentration is less than about 1.0 M sodium ion, such as about0.01-1.0 M sodium ion concentration (or other salts) at pH 7.0 to 8.3and the temperature is at least about 30° C. for short probes (e.g.,about 10-50 nucleotides) and at least about 60° C. for long probes(e.g., greater than about 50 nucleotides). Stringent conditions may alsobe achieved with the addition of destabilizing agents such as formamide.For selective or specific hybridization, a positive signal may be atleast 2 to 10 times background hybridization. Exemplary stringenthybridization conditions include the following: 50% formamide, 5×SSC,and 1% SDS, incubating at 42° C., or, 5×SSC, 1% SDS, incubating at 65°C., with wash in 0.2×SSC, and 0.1% SDS at 65° C. However, severalfactors other than temperature, such as salt concentration, caninfluence the stringency of hybridization and one skilled in the art cansuitably select the factors to accomplish a similar stringency.

As used herein the term “reference value” refers to a value thatstatistically correlates to a particular outcome when compared to anassay result. In preferred embodiments, the reference value isdetermined from statistical analysis of studies that compare microRNAexpression with known clinical outcomes. The reference value may be athreshold score value or a cutoff score value. Typically a referencevalue will be a threshold above (or below) which one outcome is moreprobable and below which an alternative threshold is more probable.

In one embodiment, a reference level may be one or more circulatingmiRNA levels expressed as an average of the level of the circulatingmiRNA from samples taken from a control population of healthy(disease-free) subjects. In another embodiment, the reference level maybe the level in the same subject at a different time, e.g., before thepresent assay, such as the level determined prior to the subjectdeveloping the disease or prior to initiating therapy. In general,samples are normalized by a common factor. For example, acellular bodyfluid samples are normalized by volume body fluid and cell-containingsamples are normalized by protein content or cell count. Nucleic acidsamples may also be normalized relative to an internal control nucleicacid.

As disclosed herein, the difference of the level of one or moremicroRNAs is indicative of a disease or a stage thereof. The phrase“difference of the level” refers to differences in the quantity of aparticular marker, such as a nucleic acid, in a sample as compared to acontrol or reference level. For example, the quantity of a particularbiomarker may be present at an elevated amount or at a decreased amountin samples of patients with a neoplastic disease compared to a referencelevel. In one embodiment, a “difference of a level” may be a differencebetween the quantity of a particular biomarker present in a sample ascompared to a control (e.g., reference value) of at least about 1%, 2%,3%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 50%, 60%, 75%, 80% 100%,150%, 200%, or more. In one embodiment, a “difference of a level” may bea statistically significant difference between the quantities of abiomarker present in a sample as compared to a control. For example, adifference may be statistically significant if the measured level of thebiomarker falls outside of about 1.0 standard deviation, about 1.5standard deviations, about 2.0 standard deviations, or about 2.5 standdeviations of the mean of any control or reference group. With respectto miRNA measurement, the level may be measured from real-time PCR asthe Ct value, which may be normalized to a ΔCt value as described in theExamples below.

EXAMPLE 1

In this example, microRNA microarray screening was conducted to identifymicroRNAs whose expression levels were altered in pancreatic cancerpatients.

Briefly, total RNAs were isolated from serum samples of 30 humans andsubjected to global miRNA profiling using microarray that was designedto sample the current miRNA sequence information available to date,Sanger miRBase Release 16(http://www.mirbase.org/cgi-bin/mirna_summary.pI?org=hsa). Themicroarray was designed to detect close to 1000 human miRNA sequences.The serum samples were derived from 10 healthy subject, 10 pancreaticcancer patients (including 9 having Stage 2A/2B pancreatic cancer and 1having neuroendocrine tumor), and 10 high risk subjects.

More specifically, 2,576 human miRNA were screening. It was found thatabout 290 human serum miRNAs showed high intensity and met the cutoffthreshold value. Among them, 116 miRNAs were identified as significantmicroRNA signatures for pancreatic cancer blood plasma. See Table 2below, where the 116 miRNA are ranked based on the significance in foldchange between Pancreatic Cancer and Healthy Control or between HighRisk Group and Healthy Control. Of these 116 significant mi-RNAs, atleast the top 30 miRNAs showed about 2 folds or more changes (up ordown).

Furthermore, as shown in Table 2, the microRNAs can be grouped into twopanels based on their values for “Fold Change between Pancreatic Cancerand Healthy Control.” Specifically, the microRNAs in the first panelwere unregulated in the pancreatic cancer patients and their “FoldChange vs Pancreatic Cancer and Healthy Control” values are greater than1.0; the microRNAs in the second panel were down-regulated in thepancreatic cancer patients and their “Fold Change vs Pancreatic Cancerand Healthy Control” values are less than 1.0.

Unsupervised clustering using 16 miRNAs (based on fold and p value)illustrated that the majority (8/9) of pancreatic cancer subjectssegregated from healthy subjects. See FIG. 1. It was also found that thesingle pancreatic neuroendocrine tumor segregated within the cluster ofhealthy subjects.

Furthermore, a candidate miRNA signature of 12 individual miRNAs wasidentified as being able to distinguish pancreatic cancer subjects fromhealthy subjects. This signature was identified based the criteria shownbelow in pancreatic cancer subjects as compared to healthy subjects: (i)Up-regulated>3.1-fold, (ii) p-value<0.005, (iii) Sensitivity: >77% fordetecting the cancer subjects, and (iv) Specificity :>70% for detectinghealthy subjects based on preliminary receiver operating characteristic(ROC) analysis. This candidate miRNA signature of 12 individual miRNAsdiffers from miRNAs previously reported in Bloomston et al., JAMA2007;297:1901-8; Szafranska et al., Oncogene 2007;26:4442-52; Szafranskaet al., Clin Chem. 2008;54:1716-24; and Lee et al., Int J Cancer.2007;120:1046-54. Those miRNAs described in the articles were identifiedfrom microarray analyses of pancreatic cancer biopsies of end-stagesubjects using probes designed to detect fewer numbers of microRNAsbased on early releases of miRBase.

TABLE 2 Fold Fold Change Change Pancreatic High Risk SEQ Cancer vsGroup vs S16_hsa_ S16_hsa_ ID Healthy Healthy miRNA_name MIMAT_ID NO:S16_hsa_miRNA_sequence Control Control P FDR rank hsa-miR-3184MIMAT0015064   8 UGAGGGGCCUCAGACCGAGCUUUU 3.76 0.60 0.00E-00 1.00E-03  1 hsa-miR-642b MIMAT0018444   4 AGACACAUUUGGAGAGGGACCC 2.91 0.906.00E-05 6.80E-03   2 hsa-miR-1909 MIMAT0007883   9CGCAGGGGCCGGGUGCUCACCG 2.76 0.69 7.00E-05 6.80E-03   3 hsa-miR-486-5pMIMAT0002177   3 UCCUGUACUGAGCUGCCCCGAG 0.37 1.06 2.70E-04 1.77E-02   4hsa-miR-711 MIMAT0012734  10 GGGACCCAGGGAGAGACGUAAG 2.61 0.64 3.00E-041.77E-02   5 hsa-miR-3125 MIMAT0014988  11 UAGAGGAAGCUGUGGAGAGA 3.914.40E-04 2.13E-02   6 hsa-miR-18b MIMAT0001412  12UAAGGUGCAUCUAGUGCAGUUAG 0.38 1.57 5.10E-04 2.13E-02   7 hsa-miR-762MIMAT0010313  13 GGGGCUGGGGCCGGGGCCGAGC 2.24 0.78 7.40E-04 2.36E-02   8hsa-miR-3154 MIMAT0015028  14 CAGAAGGGGAGUUGGGAGCAGA 3.36 0.87 7.80E-042.36E-02   9 hsa-miR-486-3p MIMAT0004762  15 CGGGGCAGCUCAGUACAGGAU 1.108.10E-04 2.36E-02  10 hsa-miR-18a MIMAT0000072   1UAAGGUGCAUCUAGUGCAGAUAG 0.41 1.59 9.70E-04 2.56E-02  11 hsa-miR-4253MIMAT0016882  16 AGGGCAUGUCCAGGGGGU 2.57 0.97 1.09E-03 2.58E-02  12hsa-miR-1288 MIMAT0005942  17 UGGACUGCCCUGAUCUGGAGA 0.43 0.05 1.23E-032.58E-02  13 hsa-miR-885-5p MIMAT0004947   6 UCCAUUACACUACCCUGCCUCU 2.520.62 1.27E-03 2.58E-02  14 hsa-miR-7 MIMAT0000252   5UGGAAGACUAGUGAUUUUGUUGU 0.78 1.34E-03 2.58E-02  15 hsa-miR-26bMIMAT0000083  18 UUCAAGUAAUUCAGGAUAGGU 0.32 1.75 1.83E-03 3.32E-02  16hsa-miR-301a MIMAT0000688  19 CAGUGCAAUAGUAUUGUCAAAGC 0.46 1.63 2.03E-033.47E-02  17 hsa-miR-106b MIMAT0000680  20 UAAAGUGCUGACAGUGCAGAU 0.471.69 2.83E-03 4.24E-02  18 hsa-miR-646 MIMAT0003316  21AAGCAGCUGCCUCUGAGGC 0.45 0.54 2.84E-03 4.24E-02  19 hsa-miR-1295MIMAT0005885  22 UUAGGCCGCAGAUCUGGGUGA 0.46 0.48 2.93E-03 4.24E-02  20hsa-miR-20b MIMAT0001413  23 CAAAGUGCUCAUAGUGCAGGUAG 0.39 1.97 4.34E-035.59E-02  21 hsa-miR-93 MIMAT0000093  24 CAAAGUGCUGUUCGUGCAGGUAG 0.451.98 4.44E-03 5.59E-02  22 hsa-miR-16 MIMAT0000069  25UAGCAGCACGUAAAUAUUGGCG 0.34 0.61 4.60E-03 5.59E-02  23 hsa-miR-3188MIMAT0015070  26 AGAGGCUUUGUGCGGAUACGGGG 2.25 0.84 4.64E-03 5.59E-02  24hsa-miR-106a MIMAT0000103  27 AAAAGUGCUUACAGUGCAGGUAG 0.44 2.47 5.63E-035.59E-02  25 hsa-miR-17 MIMAT0000070  28 CAAAGUGCUUACAGUGCAGGUAG 0.452.56 5.74E-03 5.59E-02  26 hsa-miR-1468 MIMAT0006789  29CUCCGUUUGCCUGUUUCGCUG 0.49 0.12 5.74E-03 5.59E-02  27 hsa-miR-19bMIMAT0000074  30 UGUGCAAAUCCAUGCAAAACUGA 0.46 1.08 5.80E-03 5.59E-02  28hsa-miR-193b MIMAT0002819  31 AACUGGCCCUCAAAGUCCCGCU 2.07 0.77 6.22E-035.59E-02  29 hsa-miR-194 MIMAT0000460  32 UGUAACAGCAACUCCAUGUGGA 1.971.11 6.22E-03 5.59E-02  30 hsa-miR-150 MIMAT0000451  33UCUCCCAACCCUUGUACCAGUG 0.48 2.01 6.25E-03 5.59E-02  31 hsa-miR-16-2*MIMAT0004518  34 CCAAUAUUACUGUGCUGCUUUA 0.48 0.98 6.35E-03 5.59E-02  32hsa-let-7g MIMAT0000414  35 UGAGGUAGUAGUUUGUACAGUU 0.33 2.91 6.55E-035.59E-02  33 hsa-miR-103-2* MIMAT0009196  36 AGCUUCUUUACAGUGCUGCCUUG0.51 0.74 6.55E-03 5.59E-02  34 hsa-miR-3937 MIMAT0018352  37ACAGGCGGCUGUAGCAAUGGGGG 2.04 1.09 6.99E-03 5.76E-02  35 hsa-miR-548oMIMAT0005919  38 CCAAAACUGCAGUUACUUUUGC 0.45 0.68 7.14E-03 5.76E-02  36hsa-let-7i MIMAT0000415  39 UGAGGUAGUAGUUUGUGCUGUU 0.33 2.04 7.39E-035.79E-02  37 hsa-miR-373* MIMAT0000725  40 ACUCAAAAUGGGGGCGCUUUCC 1.900.55 8.37E-03 5.87E-02  38 hsa-miR-484 MIMAT0002174  41UCAGGCUCAGUCCCCUCCCGAU 0.54 0.69 8.67E-03 5.87E-02  39 hsa-miR-338-3pMIMAT0000763  42 UCCAGCAUCAGUGAUUUUGUUG 0.71 8.73E-03 5.87E-02  40hsa-miR-1282 MIMAT0005940  43 UCGUUUGCCUUUUUCUGCUU 0.50 0.26 8.95E-035.87E-02  41 hsa-miR-4327 MIMAT0016889  44 GGCUUGCAUGGGGGACUGG 1.95 1.099.05E-03 5.87E-02  42 hsa-miR-550b MIMAT0018445  45 UCUUACUCCCUCAGGCACUG1.15 9.38E-03 5.87E-02  43 hsa-miR-106b* MIMAT0004672  46CCGCACUGUGGGUACUUGCUGC 0.83 9.48E-03 5.87E-02  44 hsa-miR-663MIMAT0003326  47 AGGCGGGGCGCCGCGGGACCGC 1.88 1.10 9.59E-03 5.87E-02  45hsa-miR-17* MIMAT0000071  48 ACUGCAGUGAAGGCACUUGUAG 0.51 1.05 9.60E-035.87E-02  46 hsa-miR-30c-1* MIMAT0004674  49 CUGGGAGAGGGUUGUUUACUCC 2.310.34 9.86E-03 5.87E-02  47 hsa-miR-665 MIMAT0004952  50ACCAGGAGGCUGAGGCCCCU 1.87 0.86 1.00E-02 5.87E-02  48 hsa-miR-363MIMAT0000707  51 AAUUGCACGGUAUCCAUCUGUA 0.44 1.56 1.04E-02 5.87E-02  49hsa-miR-144 MIMAT0000436  52 UACAGUAUAGAUGAUGUACU 0.46 1.19 1.06E-025.87E-02  50 hsa-miR-514b-5p MIMAT0015087  53 UUCUCAAGAGGGAGGCAAUCAU2.09 0.66 1.09E-02 5.87E-02  51 hsa-miR-324-5p MIMAT0000761  54CGCAUCCCCUAGGGCAUUGGUGU 0.71 1.09E-02 5.87E-02  52 hsa-miR-92aMIMAT0000092  55 UAUUGCACUUGUCCCGGCCUGU 0.55 1.11 1.09E-02 5.87E-02  53hsa-miR-183 MIMAT0000261  56 UAUGGCACUGGUAGAAUUCACU 1.16 1.12E-025.87E-02  54 hsa-miR-498 MIMAT0002824  57 UUUCAAGCCAGGGGGCGUUUUUC 1.860.61 1.15E-02 5.87E-02  55 hsa-miR-652 MIMAT0003322  58AAUGGCGCCACUAGGGUUGUG 0.52 1.14 1.17E-02 5.87E-02  56 hsa-miR-1914*MIMAT0007890  59 GGAGGGGUCCCGCACUGGGAGG 1.89 0.62 1.18E-02 5.87E-02  57hsa-miR-451 MIMAT0001631  60 AAACCGUUACCAUUACUGAGUU 0.49 0.44 1.18E-025.87E-02  58 hsa-miR-25 MIMAT0000081  61 CAUUGCACUUGUCUCGGUCUGA 0.541.57 1.20E-02 5.87E-02  59 hsa-miR-4270 MIMAT0016900  62UCAGGGAGUCAGGGGAGGGC 1.95 0.78 1.22E-02 5.87E-02  60 hsa-miR-1202MIMAT0005865  63 GUGCCAGCUGCAGUGGGGGAG 2.03 0.58 1.23E-02 5.87E-02  61hsa-miR-1908 MIMAT0007881  64 CGGCGGGGACGGCGAUUGGUC 1.84 0.86 1.27E-025.87E-02  62 hsa-miR-1268 MIMAT0005922  65 CGGGCGUGGUGGUGGGGG 1.90 0.791.28E-02 5.87E-02  63 hsa-miR-532-5p MIMAT0002888  66CAUGCCUUGAGUGUAGGACCGU 0.53 1.17 1.30E-02 5.90E-02  64 hsa-miR-28-5pMIMAT0000085  67 AAGGAGCUCACAGUCUAUUGAG 0.93 1.35E-02 5.91E-02  65hsa-miR-29b MIMAT0000100  68 UAGCACCAUUUGAAAUCAGUGUU 0.53 1.17 1.35E-025.91E-02  66 hsa-let-7c MIMAT0000064  69 UGAGGUAGUAGGUUGUAUGGUU 0.412.31 1.36E-02 5.91E-02  67 hsa-miR-20a MIMAT0000075  70UAAAGUGCUUAUAGUGCAGGUAG 0.41 2.35 1.45E-02 6.08E-02  68 hsa-miR-122MIMAT0000421  71 UGGAGUGUGACAAUGGUGUUUG 2.33 1.12 1.47E-02 6.08E-02  69hsa-miR-548k MIMAT0005882  72 AAAAGUACUUGCGGAUUUUGCU 0.53 0.53 1.52E-026.08E-02  70 hsa-miR-149* MIMAT0004609  73 AGGGAGGGACGGGGGCUGUGC 1.881.04 1.53E-02 6.08E-02  71 hsa-miR-4289 MIMAT0016920  74GCAUUGUGCAGGGCUAUCA 0.55 0.72 1.53E-02 6.08E-02  72 hsa-miR-150*MIMAT0004610  75 CUGGUACAGGCCUGGGGGACAG 1.84 0.70 1.53E-02 6.08E-02  73hsa-miR-223* MIMAT0004570  76 CGUGUAUUUGACAAGCUGAGUU 0.96 1.59E-026.11E-02  74 hsa-miR-18a* MIMAT0002891  77 ACUGCCCUAAGUGCUCCUUCUGG 0.560.65 1.60E-02 6.11E-02  75 hsa-miR-550a* MIMAT0003257  78UGUCUUACUCCCUCAGGCACAU 0.93 1.60E-02 6.11E-02  76 hsa-miR-454*MIMAT0003884  79 ACCCUAUCAAUAUUGUCUCUGC 0.52 0.13 1.62E-02 6.11E-02  77hsa-miR-133b MIMAT0000770  80 UUUGGUCCCCUUCAACCAGCUA 0.54 0.48 1.73E-026.31E-02  78 hsa-miR-1469 MIMAT0007347  81 CUCGGCGCGGGGCGCGGGCUCC 1.761.11 1.74E-02 6.31E-02  79 hsa-miR-939 MIMAT0004982  82UGGGGAGCUGAGGCUCUGGGGGUG 2.02 1.36 1.74E-02 6.31E-02  80 hsa-miR-186MIMAT0000456  83 CAAAGAAUUCUCCUUUUGGGCU 0.57 0.71 1.78E-02 6.35E-02  81hsa-miR-3162 MIMAT0015036  84 UUAGGGAGUAGAAGGGUGGGGAG 2.18 0.90 1.80E-026.35E-02  82 hsa-miR-26a MIMAT0000082  85 UUCAAGUAAUCCAGGAUAGGCU 0.481.83 1.82E-02 6.35E-02  83 hsa-let-7e MIMAT0000066  86UGAGGUAGGAGGUUGUAUAGUU 0.52 0.92 1.85E-02 6.37E-02  84 hsa-miR-3621MIMAT0018002  87 CGCGGGUCGGGGUCUGCAGG 1.79 0.88 1.88E-02 6.37E-02  85hsa-miR-92b MIMAT0003218  88 UAUUGCACUCGUCCCGGCCUCC 0.56 1.22 1.90E-026.37E-02  86 hsa-miR-15b MIMAT0000417  89 UAGCAGCACAUCAUGGUUUACA 0.511.51 1.93E-02 6.37E-02  87 hsa-miR-3202 MIMAT0015089  90UGGAAGGGAGAAGAGCUUUAAU 2.13 0.60 1.93E-02 6.37E-02  88 hsa-miR-146b-5pMIMAT0002809  91 UGAGAACUGAAUUCCAUAGGCU 0.55 1.36 2.03E-02 6.61E-02  89hsa-miR-4306 MIMAT0016858  92 UGGAGAGAAAGGCAGUA 0.58 1.37 2.11E-026.80E-02  90 hsa-miR-590-5p MIMAT0003258  93 GAGCUUAUUCAUAAAAGUGCAG 0.571.26 2.28E-02 7.25E-02  91 hsa-miR-339-3p MIMAT0004702  94UGAGCGCCUCGACGACAGAGCCG 0.83 2.44E-02 7.66E-02  92 hsa-miR-15aMIMAT0000068  95 UAGCAGCACAUAAUGGUUUGUG 0.44 1.41 2.46E-02 7.66E-02  93hsa-let-7b MIMAT0000063  96 UGAGGUAGUAGGUUGUGUGGUU 0.47 2.34 2.53E-027.81E-02  94 hsa-miR-551a MIMAT0003214  97 GCGACCCACUCUUGGUUUCCA 0.540.34 2.88E-02 8.53E-02  95 hsa-miR-342-3p MIMAT0000753  98UCUCACACAGAAAUCGCACCCGU 0.59 1.45 2.88E-02 8.53E-02  96 hsa-miR-362-5pMIMAT0000705  99 AAUCCUUGGAACCUAGGUGUGAGU 0.79 2.91E-02 8.53E-02  97hsa-miR-199a-5p MIMAT0000231 100 CCCAGUGUUCAGACUACCUGUUC 0.56 1.082.91E-02 8.53E-02  98 hsa-miR-1293 MIMAT0005883 101UGGGUGGUCUGGAGAUUUGUGC 0.56 0.49 2.93E-02 8.53E-02  99 hsa-miR-96MIMAT0000095 102 UUUGGCACUAGCACAUUUUUGCU 0.73 2.94E-02 8.53E-02 100hsa-miR-3911 MIMAT0018185 103 UGUGUGGAUCCUGGAGGAGGCA 1.76 0.80 3.00E-028.61E-02 101 hsa-miR-122* MIMAT0004590 104 AACGCCAUUAUCACACUAAAUA 1.833.08E-02 8.63E-02 102 hsa-miR-185 MIMAT0000455 105UGGAGAGAAAGGCAGUUCCUGA 0.60 1.50 3.09E-02 8.63E-02 103 hsa-miR-195MIMAT0000461 106 UAGCAGCACAGAAAUAUUGGC 0.48 1.42 3.09E-02 8.63E-02 104hsa-miR-29c* MIMAT0004673 107 UGACCGAUUUCUCCUGGUGUUC 0.76 3.14E-028.63E-02 105 hsa-miR-140-3p MIMAT0004597 108 UACCACAGGGUAGAACCACGG 0.571.63 3.15E-02 8.63E-02 106 hsa-miR-1290 MIMAT0005880 109UGGAUUUUUGGAUCAGGGA 1.71 0.67 3.23E-02 8.76E-02 107 hsa-miR-182MIMAT0000259 110 UUUGGCAAUGGUAGAACUCACACU 0.58 1.57 3.29E-02 8.82E-02108 hsa-miR-205 MIMAT0000266 111 UCCUUCAUUCCACCGGAGUCUG 0.56 0.713.43E-02 9.01E-02 109 hsa-miR-638 MIMAT0003308 112AGGGAUCGCGGGCGGGUGGCGGCCU 1.71 1.05 3.44E-02 9.01E-02 110 hsa-miR-1182MIMAT0005827 113 GAGGGUCUUGGGAGGGAUGUGAC 1.73 0.60 3.45E-02 9.01E-02 111hsa-miR-103 MIMAT0000101 114 AGCAGCAUUGUACAGGGCUAUGA 0.49 1.81 3.54E-029.17E-02 112 hsa-miR-223 MIMAT0000280 115 UGUCAGUUUGUCAAAUACCCCA 0.501.21 3.66E-02 9.39E-02 113 hsa-miR-423-3p MIMAT0001340 116AGCUCGGUCUGAGGCCCCUCAGU 0.61 1.08 3.77E-02 9.58E-02 114 hsa-miR-128MIMAT0000424 117 UCACAGUGAACCGGUCUCUUU 0.62 1.20 3.87E-02 9.77E-02 115hsa-miR-199a- MIMAT0000232; 118 ACAGUAGUCUGCACAUUGGUUA 0.50 1.503.92E-02 9.80E-02 116 3p; hsa-miR- MIMAT0004563 199b-3p

EXAMPLE 2

The above-described microarray data is qualitative in nature. It isimportant to submit the findings to a quantitative interrogation such asRTqPCR. Thus, in this example, assays were carried out for confirmingthe above-mentioned 12 microRNAs through an independent method so as toachieve the goal of identifying signature microRNAs as a blood basedmicroRNA biomarker.

To that end, the TaqMan™ MicroRNA Assays (Applied Biosystems, FosterCity, Calif.) were used to verify the microRNAs in expanded sample pool.Expanding the study sample as outlined below allowed for greatervalidation and new cohorts for data analysis. More specifically,analysis of blood from an additional 65 subjects, including 30 stage2A/2B pancreatic cancer, 10 high risk subjects, 10 unrelated malignanttumors, 5 benign cystic neoplasm of the pancreas, 5 chronicpancreatitis, and 5 healthy volunteers.

Of particular interest, inclusion of the high risk cohort hassignificant utility to gain critical insight into early detection. Sinceapproximately 10% of pancreatic cancers are hereditary in origin (Kleinet al. Cancer J 2001;7:266-73; Bartsch et al. Int J Cancer2004;110:902-6; and Hemminki et al. Int J Cancer 2003;103:525-30) and insome individuals the lifetime risk of pancreatic cancer approaches 50%(Rulyak et al. Pancreatology 2001;1(5):477-85), a microRNA signature forscreening and surveillance would be significant.

Briefly, whole blood was obtained from each patient and plasma extractedusing a standard method (Ho et al., Transl Oncol. 2010;3:109-113). Then,real-time quantitative polymerase chain reaction (real-time qPCR) formiRNA expression analysis was carried out. The levels of theabove-mentioned miRs were determined by stem loop real-time qPCR usinggene-specific TaqMan™ minor groove binding (MGB) primers according tothe TaqMan MicroRNA Assay protocol (Applied Biosystems, Foster City,Calif.).

Each miRNA was amplified individually and in triplicate. Defaultthreshold settings were used to determine threshold cycle (CT).Comparative CT method (2^(−ΔCT)) was used for relative quantification ofmiRNA expression. MiR-3196 was used as normalizer because this miRNAshowed minimal variation. The relative expression levels of each miRNAin comparison to the normalizer were then calculated using the formula2^(−ΔCT) where ΔCT represents the difference between each target geneand the normalizer (average CT for the target minus average CT formiR-3196). Shown below is a data processing procedure:

-   -   1. Raw CT values from 384 wells and 96 wells of the RT-PCR        plates were exported from RQ Manager 1.2.1 to obtain ‘Raw’        values, they were presented in ‘qPCR_miR*’ tabs.    -   2. Excel formulas were used to pull CT values from the ‘Raw’        data to obtain the ‘Raw CTs’ values.    -   3. The undetermined wells were replaced with ‘ND’ to obtain the        ‘Adjusted-CTs’ values and correlation between 384 well and 96        well data was computed.    -   4. For each sample, the sample mean was calculated by averaging        the triplicate data points and ‘ND’ were substituted with the        least detected CT value (CT-->40) to obtain the ‘MeanCTs’        values.    -   5. miR-3196 which had low stdevs across the samples was chosen        as the Normalization Control miRNA.    -   6. For each miRNA, the miRNA mean across the sample was        calculated including the normalization control.    -   7. For each sample, the mean CT of the normalization control        (miR-3196) was subtracted from the sample CT value to obtain the        ‘ΔCT’ values.    -   8. The grand mean of the normalization control was subtracted        from each miRNA mean to obtain the ‘ΔCT’ value of the miRNA        mean.    -   9. For each sample, the ‘ΔCT’ value of the miRNA mean was        subtracted from sample ‘ΔCT’ value to obtain the ‘ΔΔCT’ values.    -   10. Relative Quantities (RQ) were calculated using the formula        RQ=2̂−(ΔΔCT), using the ‘ΔΔCT’ values, and presented in the ‘RQ’        tab.    -   11. The ANOVA test results (see Statistical Analysis box below)        were also presented in the ‘RQ’ tab.

For statistical analysis, the Anova analysis was used based on a one-wayanova package from R. For each miRNA, the anova was tested across threedifferent groups (Cancer, Healthy Control and High-risk). Normalizeddata sets from both RTQ-PCR and Microarray were used for‘RTQPCR-Microarray-Comparison.'ΔCT’ values were used as the normalizeddataset for RQPCR. The results are shown in Table 3 below. As shown inthe table, miR-18a, miR-22, miR-486, miR-642b, miR-7, and miR-885-5pexhibited higher expression levels in cancer patients than in healthcontrol.

The foregoing examples and description of the preferred embodimentsshould be taken as illustrating, rather than as limiting the presentinvention as defined by the claims. As will be readily appreciated,numerous variations and combinations of the features set forth above canbe utilized without departing from the present invention as set forth inthe claims. Such variations are not regarded as a departure from thescope of the invention, and all such variations are intended to beincluded within the scope of the following claims. All references citedherein are incorporated herein in their entireties.

TABLE 3 RTQ-PCR Fold Changes Microarray High Cancer Fold Changes CancerRisk vs. Mean Cancer High Cancer Mean miRNA vs. vs. High Healthy Highvs. Risk vs. vs. High Healthy High Name Control Control Risk CancerControl Risk Control Control Risk Cancer Control Risk miR-18a 3.99 0.894.50 0.076 2.074 2.247 0.41 1.60 0.26 8.320 9.615 10.289 miR-22 10.500.34 30.57 −2.782 0.610 2.152 1.21 1.28 0.94 14.148 13.871 14.232miR-3196 1.00 1.00 1.00 0.000 0.000 0.000 1.45 1.34 1.08 13.260 12.72013.143 miR-3648 0.76 0.38 2.00 4.653 4.261 5.656 1.41 0.98 1.43 14.85014.359 14.330 miR-4253 0.60 0.69 0.87 5.037 4.295 4.837 2.58 0.97 2.6512.481 11.115 11.074 miR-486 2.90 1.74 1.67 −6.528 −4.989 −5.786 0.371.06 0.35 13.199 14.628 14.706 miR-642b 1.37 0.18 7.46 2.769 3.227 5.6682.90 0.89 3.25 10.792 9.255 9.093 miR-7 11.44 1.04 11.05 0.934 4.4504.400 0.42 0.78 0.54 5.847 7.105 6.745 miR-885-5p 11.42 0.87 13.17−0.136 3.377 3.583 2.52 0.62 4.05 9.183 7.851 7.166 Note: Mean value forRTQ-PCR was calculated from the ‘ΔCT’ value. For correlation purpose,two samples c011-b and HR011-b (011-HR) that were not present in themicroarray study were dropped Note: Mean Value for Microarray wascalculated from the final Log2-transformed, averaged and normalizedprobe intensities.

What is claimed is:
 1. A method for determining whether a subject has,or is at risk of having, a cellular proliferative disorder, comprising(i) obtaining from the subject a sample and (ii) determining in thesample the expression level of a first microRNA, the first microRNAbeing selected from a panel of up-regulated microRNAs consisting ofmiR-18a, miR-22, miR-486, miR-642b, miR-7, and miR-885-5p, whereby thesubject is determined to have, or to be at risk of having, the cellularproliferative disorder if the expression level of the first microRNAselected from the panel is above a predetermined reference value.
 2. Themethod of claim 1, wherein the cellular proliferative disorder is acancer selected from the group consisting of pancreatic cancer, coloncancer, breast cancer, prostate cancer, hepatocellular carcinoma,melanoma, lung cancer, glioblastoma, brain tumor, hematopoieticmalignancies, retinoblastoma, renal cell carcinoma, head and neckcancer, cervical cancer, esophageal cancer, and squamous cell carcinoma.3. The method of claim 1, wherein the disorder is a pancreatic cancer.4. The method of claim 1, wherein the predetermined reference value isobtained from a control subject that does not have the cellularproliferative disorder.
 5. The method of claim 1, wherein the subject isone with a high risk of having the cellular proliferative disorder. 6.The method of any of claims 1, wherein the sample is a body fluidsample.
 7. The method of claim 6, where in the same is selected from thegroup consisting of blood, serum, and plasma.
 8. The method of claim 7,wherein the sample is a blood sample.
 9. The method of any of claims 1,wherein the sample comprises pancreatic tissue, pancreatic tumor,pancreatic cells, or pancreatic juice.
 10. The method of any of claims1, wherein the method further comprises determining in the sample theexpression level of a second microRNA.